Advancing behavioural science

Tools and techniques to advance behavioural science.

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Defining and selecting behaviours to change

The Behaviour Change Wheel (BCW): From behavioural diagnosis to intervention design

The Behaviour Change Wheel (Michie et al., 2014)

The BCW was developed from 19 frameworks of behaviour change identified in a systematic literature review. It consists of three layers.
The hub identifies the sources of the behaviour that could prove fruitful targets for intervention. It uses the COM-B ('capability', 'opportunity', 'motivation' and 'behaviour') model. This model recognises that behaviour is part of an interacting system involving all these components. Interventions need to change one or more of them in such a way as to put the system into a new configuration and minimise the risk of it reverting.
Surrounding the hub is a layer of nine intervention functions to choose from based on the particular COM-B analysis one has undertaken.
The outer layer, the rim of the wheel, identifies seven policy categories that can support the delivery of these intervention functions.

The BCW provides a systematic way of identifying relevant intervention functions and policy categories based on what is understood about the target behaviour. General intervention functions can be translated into specific techniques for changing behaviour, through using the behaviour change technique taxonomy.

Find out more on the BCW website, where you can also order the book 'The Behaviour Change Wheel: A Guide to Designing Interventions'.

The COM-B model of behaviour

Once a target behaviour has been identified, the next step in the BCW process is to understand the influences underlying its performance. COM-B is a simple model of behaviour which shows that people must have Capability, Opportunity and Motivation to perform a behaviour. A COM-B diagnosis involves identifying what needs to change in a person’s capability, opportunity, and/or motivation in order to perform the behaviour. This could be done through surveys, interviews, and focus groups. You can read more about COM-B in this paper.

Selecting behaviour change techniques

Work at the Centre for Behaviour Change has identified 93 Behaviour change techniques (BCTs). BCTs can be used on their own or in combination with each other. Most interventions to change behaviour contain more than one BCT. We have developed the following tools for identifying relevant BCTs that would be suitable for including in a particular type of intervention:

The Behaviour Change Technique Taxonomy (BCTT) is a taxonomy of 93 distinct BCT’s with labels, definitions and examples. BCTT offers a reliable method for specifying, interpreting and implementing the active ingredients of interventions to change behaviours that can be used by researchers and practitioners communities. Its development was funded by the Medical Research Council. You can learn more about the BCTT on the BCTT website. View a PDF version of the BCTT mapping table.

A mobile app version of the taxonomy is freely available to allow more flexible use of the BCTT. As well as listing all 93 BCTs with their definitions and examples, the App also allows users to search for the most frequently used BCTs for each Intervention Type. You can download the BCTTv1 app from the Apple Store or Google Play.

Translations: the BCTT has been translated into several languages:

Spanish translation, plus an accompanying paper on the process
Portuguese translation
Romanian translation

Evaluating an idea for an intervention

APEASE is a checklist of six criteria which can be used to evaluate the appropriateness of potential intervention types and policy options. It stands for:

Acceptability; how far an intervention or some part or aspect of it is or is likely to be liked or engaged with.
Practicability; how far an intervention or part of an intervention can or is likely to be able to be delivered as planned and at the scale intended.
Effectiveness; how far an intervention or part of an intervention achieves or is likely to achieve a desired outcome and provides value for money.
Affordability; how far an intervention or part of an intervention can or is likely to be implemented within an available budget.
Spillover effects; how far an intervention or part of an intervention has or is likely to have unintended positive or negative effects.
Equity; how far an intervention or part of an intervention affects or is likely to affect inequalities.

Ontologies

Ontologies can be used to synthesise evidence, link data sets and predict intervention outcomes in novel scenarios. Visit the HBCP / APRICOT website, to learn more about our work on ontologes, access resources and open-source tools, get training, watch webinars, and much more.

Video: What are ontologies and how are they useful in behavioural science?

Prof Susan Michie gave a plenary talk at the IBTN Conference in Montreal, which took place in May 2024. The presentation was part of the session on 'Use Of Ontologies In Behavioural Intervention Development And Testing'.

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Artificial intelligence

AI and the future of behavioural science

Prof Susan Michie (CBC Director) and Prof Robert West (CBC Associate) took part in this panel event at LSE:

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AI Tools and Resources Repository for Behavioural Researchers

AI is not a replacement for rigorous methodology, but when used thoughtfully, it can support researchers across the entire research cycle, making our work more efficient and informative. BR-UK have a repository to help you navigate the opportunities and challenges of using Artificial Intelligence (AI) in behavioural research. BR-UK have also held several webinars on AI in behavioural research, which you can catch up with on their website.

Artificial Intelligence in Public Health Decisions

The AI in Public Health Decisions Toolkit

This toolkit contains a set of resources to support people to critically question the use of an Artificial Intelligence (AI) system. The resources can be used to help people decide how much they want public health decision makers to trust an AI system.

General research tools

Involving young people in research (paper): This paper (lead author: Rachel Perowne, PhD student, CBC) provides a practical resource for researchers considering involving young people in the research process, and suggests what data should be collected to improve reporting on the diversity of the young people involved. (June 2024)
CONSORT Guidelines: recommendations for reporting randomized controlled trials: Consolidated Standards of Reporting Trials (CONSORT), encompasses various initiatives developed by the CONSORT Group to alleviate the problems arising from inadequate reporting of randomized controlled trials (RCTs). The main product of CONSORT is the CONSORT Statement, which is an evidence-based, minimum set of recommendations for reporting RCTs. It offers a standard way for authors to prepare reports of trial findings, facilitating their complete and transparent reporting, and aiding their critical appraisal and interpretation. (April 2025)
Better reporting of interventions: Template for Intervention Description and Replication (TIDieR) checklist and guide: Without a complete published description of interventions, clinicians and patients cannot reliably implement interventions that are shown to be useful, and other researchers cannot replicate or build on research findings. The quality of description of interventions in publications, however, is remarkably poor. To improve the completeness of reporting, and ultimately the replicability, of interventions, an international group of experts and stakeholders developed the Template for Intervention Description and Replication (TIDieR) checklist and guide. (March 2014)

Interested in gaining more in-depth knowledge?

We offer a range of training courses in behavioural science. Find out more on our training page.